Single instruction multiple data (SIMD)-based k-discrete oriented polytope (k-DOP) bounding volume collision detection method

Abstract

The invention discloses a single instruction multiple data (SIMD)-based k-discrete oriented polytope (k-DOP) bounding volume collision detection method, which comprises the following steps of: (1) constructing a bounding volume hierarchy (BVH) by using an SIMD instruction; (2) constructing a bounding volume testing tree (BVTT), and performing a bounding volume overlap test on the BVTT by using the SIMD instruction; and (3) performing accurate collision detection on a bounding volume. The instruction-level parallel processing capability of SIMD is utilized, so that the number of instructions in the collision detection operation process is reduced, the process of constructing or reconstructing the bounding volume and constructing or updating the BVH and the bounding volume overlap test process are accelerated, and collision detection time is shortened; and compared with the conventional collision detection method, the method has the advantages that: the speed can be improved by about 4 times, and the method is high in compatibility and is effectively complementary with task-level parallel processing, so that the whole parallel speed-up ratio is improved, and the method is particularly suitable for the technical fields of robot motion path planning, physical simulation, video games and the like.

Description

technical field [0001] The invention belongs to the technical field of computer detection, in particular to a SIMD (Single Instruction Multiple Data)-based k-DOP bounding box collision detection method. Background technique [0002] Bounding volume hierarchy (BVH) is an important tool for efficient collision detection for triangular mesh models. Various BVHs, such as Sphere (Sphere) tree, Axis Aligned Bounding Box (AABB) tree, Oriented Bounding Box (OBB) tree, Discrete Oriented Polyhedron (k-DOP) tree, etc. These hierarchical structures usually adopt a top-down approach It is widely used for collision detection of rigid or flexible objects. The rapid update technology of the BVH of flexible objects (such as rearrangement, dynamic or selective reconstruction, etc.) has become the focus of many researchers in this field. [0003] For flexible objects, in addition to the compactness of the bounding box, the efficiency of bounding box sorting and reconstruction is also crucial...

AI Technical Summary

Problems solved by technology

figure 1 It is a schematic diagram of the three bounding boxes of AABB, 8-DOP and OBB. For simple bounding boxes such as Sphere and AABB, the organization and construction are very fast, but the compactness is poor; for complex bounding boxes such as OBB, although relatively compact, However, the amount of calculation for sorting and construction is relatively large; as a compromise, k-DOP is both compact and efficient, so it is often used for the bounding box hierarchy of flexible objects

[0004] At present, the traditional k-DOP bounding box collision detection method uses a serial implementation to complete the collision detection. The k-DOP bounding box has too many instructions in the process of reconstruction and arrangement, and it is very time-consuming to execute. Poor real-time performance, in applications with high real-time requirements such as robot motion path planning, physical simulation, video games, etc., it cannot meet the corresponding collision detection requirements

Images